319results about How to "Eliminate false positives" patented technology

A probe attached to a customer's network collects status data and other audit information from monitored components of the network, looking for footprints or evidence of unauthorized intrusions or attacks. The probe filters and analyzes the collected data to identify potentially security-related events happening on the network. Identified events are transmitted to a human analyst for problem resolution. The analyst has access to a variety of databases (including security intelligence databases containing information about known vulnerabilities of particular network products and characteristics of various hacker tools, and problem resolution databases containing information relevant to possible approaches or solutions) to aid in problem resolution. The analyst may follow a predetermined escalation procedure in the event he or she is unable to resolve the problem without assistance from others. Various customer personnel can be alerted in a variety of ways depending on the nature of the problem and the status of its resolution. Feedback from problem resolution efforts can be used to update the knowledge base available to analysts for future attacks and to update the filtering and analysis capabilities of the probe and other systems.

A method for calculating sales trend of a product at a store shelf based on crowdsourcing, includes receiving, by a retail store server, availability data of a product measured on a shelf in the retail store from a portable device, where the availability data is in the form of a picture acquired of the product on the shelf, identifying products on the shelf using tags attached to the shelves, calculating sales velocity and sales trends of the product from the identified products, and transmitting the sales velocity and sales trend of the product to one or more third parties' systems in a supply chain of said retail store. Products and their locations on retail store shelves have been cataloged in a product database.

The invention relates to a substation equipment appearance abnormality recognition method based on a substation inspection robot. In the method, based on a power inspection robot platform (with a model number of LER-3000), relative technologies such as an image processing technology, a mode recognition technology and the like are utilized to detect images collected by power equipment, judge whether the equipment is in abnormal conditions of fouling, damage, foreign bodies and the like or not, find out a corresponding defect recognition method by analyzing the collected images, accurately and rapidly detect the abnormality of the equipment, timely report and eliminate safety hidden dangers. The substation equipment appearance abnormality recognition method based on the substation inspection robot comprises the following steps of, firstly, collecting an image of each equipment on an inspection route by the power inspection robot; secondly, carrying out registration on a processed image and a corresponding equipment reference image stored in advance; thirdly, after image registration, detecting a region with the abnormality according to a difference of the two images; and fourthly, classifying the abnormality according to characteristic parameters of the detected abnormal region.

An active implantable medical device comprising circuits for measuring trans-thoracic impedance and delivering an impedance signal varying with respiratory activity of a patient. A signal representative of the respiratory activity of the patient is delivered starting from the impedance signal, and circuits for diagnosing respiratory disorder analyze variations of the respiratory signal on a plurality of successive cycles to detect there a profile of predetermined variation in relation to a given respiratory disorder. The device also includes circuits for automatically controlling respiratory cycles with artifacts, able to identify in the impedance signal a jump of static impedance, and/or to identify in a respiratory cycle or in a sequence of respiratory cycles a predetermined singularity representative of a cycle with artifact.

Satellite images from vast historical archives are analyzed to predict severe storms. We extract and summarize important visual storm evidence from satellite image sequences in a way similar to how meteorologists interpret these images. The method extracts and fits local cloud motions from image sequences to model the storm-related cloud patches. Image data of an entire year are adopted to train the model. The historical storm reports since the year 2000 are used as the ground-truth and statistical priors in the modeling process. Experiments demonstrate the usefulness and potential of the algorithm for producing improved storm forecasts. A preferred method applies cloud motion estimation in image sequences. This aspect of the invention is important because it extracts and models certain patterns of cloud motion, in addition to capturing the cloud displacement.

A method whereby first biological entities are recognized by way of second biological entities able to bind to the first (or the first to the second), including the steps of binding first biological entities to a surface comprising an array of first electrodes selectively energizable and addressable at least in part, positioned facing at least one second electrode, bringing the second biological entities into contact with the first, these second biological entities and possibly the first being moved by means of dielectrophoretic cages generated between the electrodes, and sensing any binding activity between at least a portion of the first and of the second biological entities, preferably utilizing radiation at a first frequency to excite fluorophore groups bound to the second biological entities and detecting the emission of fluorescence at a second frequency by means of optical sensors integrated into the electrodes, the biological entities preferably being concentrated on the electrodes by the fusion of dielectrophoretic cages.

The invention relates to the technical field of optical fiber vibration sensing and in particular relates to an interference type optical fiber perimeter vibration intrusion recognition algorithm suitable for security perimeter. The interference type optical fiber perimeter vibration intrusion recognition algorithm is characterized by comprising the following operations: reading data acquired by an optical fiber vibration sensor from a data acquisition end, and normalizing the acquired data; performing empirical mode decomposition; calculating a characteristic value of an empirical mode decomposition result; detecting multiple characteristic values, judging whether intrusion exists, if so, alarming, otherwise repeating the steps 1-5 for performing recognition in the next round. Compared with the prior art, the interference type optical fiber perimeter vibration intrusion recognition algorithm has the advantages that an original signal is subjected to empirical mode decomposition, the judgment accuracy is improved, the possibility that false alarm is caused due to a certain occasional specific characteristic can be eliminated by adopting a multi-characteristic value threshold detection mode, and intrusion alarm can be accurately realized under the condition that interferences of wind, rain, vehicles and the like exist.

The invention discloses a video technology based secure and smart recognition method for a railway crossing protection zone. The method comprises the following steps: acquiring live video image data of the railway crossing protection zone in real time in a YUV mode; adopting a working codebook having characteristics of a Gaussian mixture model to perform motion detection on to-be-analyzed live video images to determine target objects; establishing an SVM (support vector machine) classifier and classifying the target objects in the to-be-analyzed live video images through the SVM classifier; judging whether the target objects are obstacles by using a multi-camera fusion coordinate transformation matrix. The video technology based secure and smart recognition method can perform secure and smart recognition on the railway crossing protection zone with more complicated geographical environment.

The invention provides an integrated pesticide residue detection pretreatment device and a pretreatment method. The device comprises a cup body, a filter, a liquid divider, a jigger, a solid phase extraction column and a test tube, wherein a crushing homogenizer is arranged in the cup body, and the bottom of the cup body is connected with the filter; the liquid divider is arranged on the bottom of the filter to be used for carrying out standing stratification on filter liquid flowing out of the filter, and the bottom of the liquid divider is connected with a three-way valve; the jigger is connected with one opening of the three-way valve to be used for quantitatively collecting a target compound, and the bottom end of the jigger is provided with a second graduating valve; the solid phase extraction column is connected on the bottom of the jigger to be used for eluting the target compound; and the test tube is used for collecting eluent and is also connected with a nitrogen flow system used for concentrating the eluent. The device and the method integrate the processes of crushing, homogenizing, ultrasonic vibrating, suction filtration, liquid-liquid extraction, solid phase extraction, concentrating constant volume and the like; the treatment method is simple and has high efficiency, and the treatment device is convenient and simple, practical and portable and can be used for on-site operation.

The invention provides a high-sensitivity method used for detecting and identifying 6 kinds of human coronavirus. The high-sensitivity method is based on exclusion of pollution caused by PCR amplification products, and is used for detecting and/or identifying human coronavirus by taking multiplex PCR-mass spectrometry as a platform. The 6 kinds of human coronavirus include HCoV-229E, HCoV-OC43, HCoV-NL63, HCoV-HKU1, SARS-CoV and MERS-CoV. Detection parts are the specific sequence domains in the genomes of the 6 kinds of human coronavirus. The high-sensitivity method is capable of realizing multiple gene detection of the 6 kinds of human coronavirus in a reaction, and increasing detectable rate; possesses advantages of high sensitivity and specificity, convenient operation, speediness, high throughput and the like; and can be used in scientific researches, clinical and epidemiological investigation.

The invention relates to a method for diagnosing fault of a wheel speed sensor of a vehicle, wherein the vehicle is provided with at least two wheels, each of which is provided with a wheel speed sensor. The method comprises the steps of obtaining the output signal of the wheel speed sensor to be examined on the wheel to be examined and the output signal of other wheel speed sensor on at least one other wheel, and diagnosing the fault of the wheel speed sensor to be examined based on the output signal of the wheel speed sensor to be examined on the wheel to be examined and the output signal of the other wheel speed sensor on the at least one other whee. The invention also relates to a controller for a vehicle and a vehicle comprising the controller. The method can be implemented in real time and is capable of diagnosing the fault successfully and preventing false start and misoperation of an ABS (Anti-lock Braking System) and/or an ESP (Electronic Stability Program) reliably, and therefore, reliable control on the wheel is further improved, and the operating performance of the vehicle is improved.

The invention discloses a method for detecting pesticide residues in sulfur-containing vegetables by an enzyme inhibition method. The method comprises the following steps of 1, preparing a standard solution, 2, preparing a sample, 3, testing control groups through the processes of adding a buffer solution into a beaker, adding dropwisely acetate or sodium hydroxide into the beaker, adjusting a pH value of the mixed solution to a pH value of 9, adding an enzyme solution and a color-developing agent into the mixed solution with a pH value of 9, shaking up, standing at a temperature of 37 DEG C for 15 minutes, adding a substrate solution into the mixed solution treated by the previous step, shaking up, and detecting an absorbance variation value delta A0 of the mixed solution undergoing a reaction at wavelength of 410 nanometers for 3 minutes by a spectrometer, 4, adding sulfur-containing vegetable sample extract into a beaker, carrying out processes same as the processes of the step 3, and detecting an absorbance variation value delta A1 of a vegetable sample mixed solution undergoing a reaction at wavelength of 410 nanometers for 3 minutes by a spectrometer, and 5, calculating an enzyme inhibition percentage according to a formula of an enzyme inhibition percentage=[(delta A0-delta A1)/delta A0]*100, wherein when the calculated enzyme inhibition percentage is great than or equal to 50%, it is shown that there are pesticide residues in the detected sulfur-containing vegetable. The method eliminates the interference of sulfides in a sulfur-containing vegetable on pesticide residue detection through adjustment of a pH value of a vegetable sample solution, can rapidly, simply and accurately detect a pesticide residue ratio of a sulfur-containing vegetable, has a low cost, and is suitable for on-site detection.

The invention provides a detecting method and device for dynamic electrocardio signal data. The method includes: preprocessing original dynamic electrocardio signal data; performing form conversion on the processed original dynamic electrocardio signal data; obtaining dynamic electrocardio signal data sections, with QRS composite waves, in the dynamic electrocardio signal data output after form conversion according to a first threshold and a second threshold, searching and positioning in the dynamic electrocardio signal data sections to obtain the QRS composite waves; updating the first threshold and the second threshold according to the original dynamic electrocardio signal data in preset time. The device comprises a preprocessing module, a form converting module and a searching module. By the method and device, artifact judgment, caused by using single threshold, in the dynamic electrocardio signal data.

The invention provides an intelligent machine tool working state identification system based on signal fusion. A sensor system is installed on a mechanical system of a machine tool and used for collecting a vibration signal, a temperature signal, a current signal and a speed signal of the machine tool; the vibration signal and the temperature signal are converted into digital signals through a data collecting system and then sent to a monitoring system, and the current signal and the speed signal are sent to the monitoring system through a numerical control system; and the monitoring system isused for controlling the vibration signal, the temperature signal, the current signal and the speed signal to be sent to a state signal database system and/or controlling the vibration signal, the temperature signal, the current signal and the speed signal to be sent to an intelligent data analysis system to achieve real-time data analysis and output an intelligent machine tool working state identification result. According to the intelligent machine tool working state identification system based on signal fusion, erroneous judgment brought by machine tool state identification obtained through signals measured by a power sensor singly is effectively eliminated, information fusion of multiple sensors is combined, a BP neural network method is adopted, therefore, errors in judgment are reduced, the system robustness is improved, and meanwhile basic conditions are provided for dynamic monitoring of the machining technology process.

The invention discloses a battery silk-screen quality detection method combining block template matching with morphological processing. The method comprises the following steps: establishing a character part template based on a morphological template matching method; extracting a battery area by applying threshold segmentation and morphological corrosion; determining an inclination angle in a mode of solving a minimum circumscribed rectangle of a battery area, searching the minimum circumscribed rectangle as a final result by adopting an equal interval rotation search algorithm, and performing reverse rotation on a deflection angle by utilizing affine transformation to perform battery correction and cutting; identifying the defects of the illustration part by adopting a difference image method; sequentially shielding picture insertion, character segmentation, character extraction and correction, character recombination and to-be-detected character skeleton extraction, identifying character part defects by adopting a difference image method, and carrying out defect detection by adopting suspicious area translation difference detection and suspicious area micro-rotation difference detection. The method is high in accuracy and low in cost, and has a certain degree of promotion effect in the field of domestic battery screen printing quality automatic detection.

The invention provides multi-lane vehicle flow counting method, device and equipment and a storage medium. The method herein comprises: acquiring first radial distances from radar to monitoring pointson lanes, wherein the radar is frequency modulated continuous wave millimeter radar; receiving reflected signals acquired by the radar from the lanes, subjecting the reflected signals and a local oscillator signal to frequency mixing to obtain medium-frequency signals, subjecting the medium-frequency signals to one-dimensional spectral analysis to obtain a first distance spectrum, acquiring a driving velocity and radar monitored distance of a target vehicle according to a preset distance amplitude threshold, the first distance spectrum, the first radial distances and a preset velocity amplitude threshold, and counting vehicle flows of the lanes within predetermined time according to the driving velocity and radar monitored distance of the target vehicle. The method, device and equipment and the storage medium can count vehicle flows of multiple lanes, response speed is high, and flow counting is accurate.

The invention discloses a method for qualitatively detecting polychlorinated biphenyl in soil and/or sediment. The method comprises the following steps of: (1) extracting the soil and/or sediment to be detected by adopting an accelerated solvent extraction method, thereby acquiring an extracting solution; (2) purifying the extracting solution through a gel permeation chromatograph, thereby acquiring an extract; (3) eluting the extract through a solid phase extraction column, and collecting the eluent; and (4) analyzing the eluent by a gas chromatograph-mass spectrometer so as to acquire full scan data, and then performing deconvolution analysis on the acquired full scan data according to a retention time locking database in the gas chromatograph-mass spectrometer, thereby qualitatively detecting the polychlorinated biphenyl in the soil and/or water body sediment to be detected.

The invention discloses a vehicle collision detection method and a vehicle control system. The vehicle collision detection method comprises the steps: the relative distance between a vehicle and an obstacle is detected; whether the relative distance is smaller than a preset distance threshold value or not is judged, and if yes, the longitudinal acceleration component and the transverse acceleration component of the vehicle within the first specified time length are obtained; the first variance of the longitudinal acceleration component and the second variance of the transverse acceleration component are determined; and if the first variance exceeds a preset first threshold value or the second variance exceeds a preset second threshold value, it is determined that a collision accident of the vehicle occurs. By implementing the vehicle collision detection method, when it is judged that the vehicle and the obstacle are excessively close, collision detection is conducted through the variances of the acceleration components in the horizontal direction of the vehicle, thus misjudgment can be reduced, and the accuracy rate of vehicle collision detection is increased.

The invention relates to a forest fire monitoring and early warning system based on infrared thermal imaging. The system comprises a plurality of thermal imaging bispectral cameras, an alarm server and an alarm client. The thermal imaging bispectral cameras include infrared thermal imaging cameras and visible light cameras that are arranged in an integrated manner. The alarm server includes a dataacquisition module, a feature extraction module, and an alarm service module which are sequentially connected. According to the invention, abnormal temperature fluctuation is determined based on temperature data collected by the thermal imaging bispectral cameras and alarming is made based on the abnormal temperature fluctuation, so that the accuracy of the fire identification alarming is improved. Meanwhile, a visible light video image of the monitoring area is displayed at the alarm client; and when a fire occurs, the staff member can check the visible light video image of the monitoring area in time to understand the fire situation in the monitoring area, so that a problem that the traditional forest fire early-warning monitoring system can only watch the hot contours of people or objects through infrared images and thus fire conditions can not be obtained accurately is solved.

An accurate detection method for the number of vehicle axles on a truck scale, which is to install an axle sensor for receiving and transmitting wheel passing information on the edge of the weighing platform of the truck scale, and receive the wheel passing information through the axle measuring sensor and It is transmitted to the microprocessor, and at the same time, the microprocessor combines the weight change of the weighing instrument of the truck scale to conduct a second judgment on the results measured by the axle sensor, and compares the front time and trailing time of the output signal of the axle sensor. The weight change measured by the weighing instrument is used as the judgment basis. When there is a significant change, it is judged that there is an axle passing; and the weight changes from light to heavy to judge that the car is moving forward, and a new axle is driving on the weighing platform; the weight is judged from heavy to light. The car is backing up, and the axle that finally drives onto the weighing platform falls out of the weighing platform. The final confirmation of the axle is determined by the computer (or microprocessor) after comparing and judging the weight measured by the truck scale weighing instrument at the arrival time of the effective signal "front" and "trailing edge" of the sensor. Misjudgment caused by the use of a single detection mode is avoided, and the accuracy is greatly improved.

The invention provides a blast furnace hearth sidewall monitoring method. According to the monitoring method, the angular heat flow densities of hearth sidewall monitoring positions are obtained, thetemperature is detected by a thermocouple arranged in carbon bricks of the hearth, based on the angular heat flow densities, the temperature, and the angular heat flow density of the hearth lining, the heat resistant values of different positions can be calculated, and the damages of the hearth sidewall can be diagnosed. According to the method, the change rules of onsite detected variables such as temperature are used to judge the situation of a blast furnace hearth; through the thermal resistant values of different positions and change rates in a certain period, the hearth can be diagnosed,the wrong judgment caused by onsite interference, fluctuation of the furnace situations, and change of cooling conditions can be eliminated, and multiple types of damages can be effectively diagnosedat the same time.

The invention discloses a method for automatically identifying wheel hub types based on structural features. The method comprises the following steps: (1) for a wheel hub in an unknown type, learning to obtain all feature parameters of the wheel hub, storing the feature parameters into a database, collecting a wheel hub visible light image through segmentation, extracting the structural feature parameters of the wheel hub in the type, achieving automatic identification of wheel hubs in different types through the parameters, (2) comparing parameters of an identified object with parameters, stored in the database, of the wheel hub types within an error allowable range when the object is identified, and obtaining a wheel hub type of the identified object when all the feature parameters are consistent, wherein inconformity of a certain parameter shows that the wheel hub can not be identified, and the type of the wheel hub does not exist in the database. According to the method, most stable features of the wheel hub are used as the identification parameters, various misjudgments in workblank wheel hub identification can be effectively avoided, and the automation degree of wheel hub production is improved.